Microglial phagolysosome dysfunction and altered neural communication amplify phenotypic severity in Prader-Willi Syndrome with larger deletion

Prader-Willi Syndrome (PWS) is a rare neurodevelopmental disorder of genetic etiology, characterized by paternal deletion of genes located at chromosome 15 in 70% of cases. Two distinct genetic subtypes of PWS deletions are characterized, where type I (PWS T1) carries four extra haploinsufficient genes compared to type II (PWS T2). PWS T1 individuals display more pronounced physiological and cognitive abnormalities than PWS T2, yet the exact neuropathological mechanisms behind these differences remain unclear. Our study employed postmortem hypothalamic tissues from PWS T1 and T2 individuals, conducting transcriptomic analyses and cell-specific protein profiling in white matter, neurons, and glial cells to unravel the cellular and molecular basis of phenotypic severity in PWS sub-genotypes. In PWS T1, key pathways for cell structure, integrity, and neuronal communication are notably diminished, while glymphatic system activity is heightened compared to PWS T2. The microglial defect in PWS T1 appears to stem from gene haploinsufficiency, as global and myeloid-specific Cyfip1 haploinsufficiency in murine models demonstrated. Our findings emphasize microglial phagolysosome dysfunction and altered neural communication as crucial contributors to the severity of PWS T1’s phenotype. Supplementary Information The online version contains supplementary material available at 10.1007/s00401-024-02714-0.


Genotyping of Cyfip1 heterozygous knockout mice
Genotyping was conducted using mouse ear lobe tissues, according to the protocol provided by GemPharmatech.For PCR to detect the Cyfip1 delta band after Cre mediated recombination, sequences of primers were set as follows: Forward: 5'-CCATTGCCAGATTTCTAGTCACATC-3'; Reverse: 5'-CATGCTCATAGCTTCTTCTCCAGC-3'.
The WT band was approximately 274bp the delta band was 378bp.

RNA isolation, sequencing and data analysis
To isolate RNA from FFPE human hypothalamic tissues, FFPE sections were placed in sterile Eppendorf tubes and rehydrated using xylene and ethanol immersion (100%, twice).The sections were thoroughly vortexed and centrifuged for 5 min at 14000 RPM at room temperature in between steps.After the final ethanol step, samples were air-dried for 10-15 minutes.Next, approximately 150 μL of PKD buffer (Qiagen) was added to the tube, followed by 10 μL of proteinase K (both for tissue and protein digestion).The Eppendorf tubes were incubated at 56°C for 15 min with constant shaking at 700 rpm.Followed by an additional shaking step at 80°C with continuous shaking.The samples were then immediately transferred to ice for 3 minutes; then centrifuged for 15 minutes at 13'500 rpm at room temperature.The supernatant was transferred to a new tube and 16 µl of DNase Booster Buffer (Qiagen) was added plus 10 µL DNase I stock solution (Qiagen), and incubated at room temperature for 15 min.Samples were then subjected to RNeasy FFPE Kit instructions (Qiagen, #73504) eluted in 14 µl RNase-free water.RNA concentration was measured using Bioanalyzer RNA Pico Chips.In terms of RNA quality, we did not observe a clear difference associated with tissue age or postmortem delay.Samples exhibiting poor RNA concentration or a low 260/280 ratio (RNA was isolated from comparable tissues) were excluded from the RNAseq study.Due to this exclusion of samples, two additional samples from control subjects were incorporated into the RNAseq study.These two subjects were not assessed using morphological parameters.Consequently, cDNA libraries were constructed for next-generation RNAseq analysis on an Illumina sequencing platform.

Images acquisition and quantitative analysis
Immunohistochemically stained images were captured with a SONY black and white camera and/or an Axio Scanner (ZEISS) and analyzed using FIJI and/or QuPath software.Images from the immunofluorescence staining were acquired using a Leica SP8-SMD confocal microscope.Blinded assessment was employed during the analysis of all images to prevent any subjective influences.Quantification of POMC-ir, NPY-ir, oxytocin-ir, and AVP-ir neurons was performed by manually outlining the area of interest based on the location of the positive signal.Depending on tissue availability usually 2-3 stained sections were available.Patient 2002-030 (PWS T1) did not have tissue available that allowed the analysis of neuropeptides in the infundibular nucleus and paraventricular nucleus and was therefore excluded from neuropeptide staining.Subsequently, the "particle analysis" software tool was used to determine the number and area of coverage of the positive signal in the outlined area.Particles between 30 µm 2 and 300 µm 2 were considered soma of neurons based on pilot studies.The total soma number was divided by the area of the outline, resulting in the soma number/mm 2 .The percentage of the outlined area occupied by immunoreactive positive particles was calculated as the percentage area masked.A similar strategy was employed for microglial markers (Iba1-ir, TMEM 119-ir, and P2Y12R-ir).In sections adjacent to those used for the neuronal markers, the number of microglia cells was determined using a pre-established (and constant) outline generated, mirroring the neuronal distribution pattern, thus covering the mediobasal hypothalamus.Positive particles larger than 20 μm 2 and smaller than 100 μm 2 (size was determined in the pilot study) were considered a positive soma of microglia cells, which allowed the calculation of soma/mm 2 and the relative percentage of coverage.Since PWS T1 subjects presented dysmorphic microglia, the calculations for this parameter were performed only on cells that presented nuclear counterstaining, to guarantee that only cells were being taken into account.A similar strategy was employed in sections from rodent brains covering the arcuate nucleus area.Synaptophysin-ir and AQP4-ir relative areas of coverage were quantified by the determined threshold of positive particles generating a masked representation of both staining in a predetermined framed area using the "pixel classification" tool in QuPath.The relative coverage of the mask in relation to the total framed area was determined and used for comparison between the groups.PLP-ir was analyzed through the "intensity features" and the average optical density of PLP in white matter shreds was used as a read out.PLP-ir myelin rings were quantified manually in a fixed outlined area (150 μm 2 ) by two independent experienced researchers with blinded assessment.Three 150 μm 2 regions of interest in the same section were then quantified and averaged by subject.
For immunofluorescence staining, three to five fields were used for each marker (co-labelling of CD68/Iba1, CTSS/Iba1, LAMP1/Iba1, PLP/Iba1, AQP4/alpha-SMA) and subsequent quantification.Images were obtained in 32bit sequential standard mode at 200 Hz in a 1024 × 1024 format.The laser intensity was constant within the image acquisition of the same marker and was determined in a pilot acquisition.Analysis of the 3D volumes of the deconvolved images was performed using the Imaris 9.0.For CD68, CTSS and LAMP1 volume analysis within Iba1ir microglial cells, CD68-ir, CTSS-ir, and LAMP1-ir particles (i.e.phagolysosomes) were analyzed in individual cells and averaged by subject.Only cells that were positive for the aforementioned markers were taken in consideration in the quantification, and 2-6 cells per field were analyzed.
Specifically, the analysis for the relative AQP4-ir surround the alpha-SMA-ir vessels was performed using QuPath software.In brief, a mask for the signal of alpha-SMA-ir and AQP4-ir particles was created using the "pixel classification" tool.No minimum particle size was imposed for either marker.Next, a circular area with a radius of 20 µm was created for every vessel annotation using the "expand annotation" tool.Then, a masked signal for AQP4ir was created, but no minimum particle area or hole size was imposed.The area of AQP4-ir signal within every expanded object in three distinct fields was calculated, transformed into a percentage in relation to the total area of the expanded annotation, and averaged by subject.
Figure preparation was performed using the Adobe Illustrator software (Adobe Systems Inc., San Jose, CA, USA).
Color correction was occasionally performed when individual pictures were assembled to figure panels for publication.No specific features within the image were enhanced, obscured, introduced, moved, or removed.